From 75d1cdccbd319b5fdba65f3bbd673032537accf4 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 11 Sep 2019 19:06:19 +0200
Subject: [PATCH] [POSTER EVAN] improve visualization of the starting years for
the poster. some refactorign for the Alps graph and cmap, from now on, we
will only remove the last 20 starting years
---
.../scm_models_data/abstract_study.py | 34 ++++++-----
.../abstract_hypercube_visualizer.py | 2 +-
.../altitude_hypercube_visualizer.py | 49 +++++++++++-----
.../main_files/main_full_hypercube.py | 2 +-
.../poster_EVAN2019/main_poster_EVAN2019.py | 57 +++++++++++++++++--
.../abstract_univariate_test.py | 10 ++++
.../margin_fits/plot/create_shifted_cmap.py | 30 +++++-----
7 files changed, 134 insertions(+), 50 deletions(-)
diff --git a/experiment/meteo_france_data/scm_models_data/abstract_study.py b/experiment/meteo_france_data/scm_models_data/abstract_study.py
index 3c7a2911..248de3d6 100644
--- a/experiment/meteo_france_data/scm_models_data/abstract_study.py
+++ b/experiment/meteo_france_data/scm_models_data/abstract_study.py
@@ -25,7 +25,8 @@ from experiment.meteo_france_data.scm_models_data.scm_constants import ALTITUDES
from experiment.meteo_france_data.scm_models_data.visualization.utils import get_km_formatter
from extreme_estimator.extreme_models.margin_model.margin_function.abstract_margin_function import \
AbstractMarginFunction
-from extreme_estimator.margin_fits.plot.create_shifted_cmap import get_color_rbga_shifted, create_colorbase_axis
+from extreme_estimator.margin_fits.plot.create_shifted_cmap import create_colorbase_axis, \
+ get_shifted_map, get_colors
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
AbstractSpatialCoordinates
@@ -50,6 +51,7 @@ class AbstractStudy(object):
"""
REANALYSIS_FLAT_FOLDER = 'SAFRAN_montagne-CROCUS_2019/alp_flat/reanalysis'
REANALYSIS_ALLSLOPES_FOLDER = 'SAFRAN_montagne-CROCUS_2019/alp_allslopes/reanalysis'
+
# REANALYSIS_FOLDER = 'SAFRAN_montagne-CROCUS_2019/postes/reanalysis'
def __init__(self, variable_class: type, altitude: int = 1800, year_min=1000, year_max=3000,
@@ -68,8 +70,6 @@ class AbstractStudy(object):
self.orientation = orientation
self.slope = slope
-
-
""" Time """
@cached_property
@@ -244,7 +244,7 @@ class AbstractStudy(object):
slope_mask = np.array(ORDERED_ALLSLOPES_SLOPES) == self.slope
allslopes_mask = altitude_mask & orientation_mask & slope_mask
# Exclude all the data corresponding to the 24th massif
- massif_24_mask =np.array(ORDERED_ALLSLOPES_MASSIFNUM) == 30
+ massif_24_mask = np.array(ORDERED_ALLSLOPES_MASSIFNUM) == 30
return allslopes_mask & ~massif_24_mask
@cached_property
@@ -283,7 +283,7 @@ class AbstractStudy(object):
@classmethod
def visualize_study(cls, ax=None, massif_name_to_value: Union[None, Dict[str, float]] = None, show=True, fill=True,
replace_blue_by_white=True,
- label=None, add_text=False, cmap=None, vmax=100, vmin=0,
+ label=None, add_text=False, cmap=None, add_colorbar=False, vmax=100, vmin=0,
default_color_for_missing_massif='gainsboro',
default_color_for_nan_values='w',
massif_name_to_color=None,
@@ -291,20 +291,23 @@ class AbstractStudy(object):
scaled=False,
fontsize=7,
axis_off=False,
- massif_name_to_hatch_boolean_list=None
+ massif_name_to_hatch_boolean_list=None,
+ norm=None,
):
if ax is None:
ax = plt.gca()
- if massif_name_to_color is None:
+ if massif_name_to_value is not None:
massif_names, values = list(zip(*massif_name_to_value.items()))
+ else:
+ massif_names, values = None, None
+
+ if massif_name_to_color is None:
+ # Load the colors
if cmap is None:
- colors = get_color_rbga_shifted(ax, replace_blue_by_white, values, label=label)
- else:
- norm = Normalize(vmin, vmax)
- create_colorbase_axis(ax, label, cmap, norm)
- m = cm.ScalarMappable(norm=norm, cmap=cmap)
- colors = [m.to_rgba(value) if not np.isnan(value) else default_color_for_nan_values for value in values]
+ cmap = get_shifted_map(vmin, vmax)
+ norm = Normalize(vmin, vmax)
+ colors = get_colors(values, cmap, vmin, vmax, replace_blue_by_white)
massif_name_to_color = dict(zip(massif_names, colors))
massif_name_to_fill_kwargs = {massif_name: {'color': color} for massif_name, color in
massif_name_to_color.items()}
@@ -366,6 +369,11 @@ class AbstractStudy(object):
if scaled:
plt.axis('scaled')
+
+ # create the colorbar only at the end
+ if add_colorbar:
+ if len(set(values)) > 1:
+ create_colorbase_axis(ax, label, cmap, norm)
if axis_off:
plt.axis('off')
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/abstract_hypercube_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/abstract_hypercube_visualizer.py
index d5e2e7c2..4cfb5d70 100644
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/abstract_hypercube_visualizer.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/abstract_hypercube_visualizer.py
@@ -126,7 +126,7 @@ class AbstractHypercubeVisualizer(object):
if not op.exists(dirname):
os.makedirs(dirname, exist_ok=True)
if tight:
- plt.savefig(filepath, bbox_inches='tight', pad_inches=-0.03, dpi=1000)
+ plt.savefig(filepath, bbox_inches='tight', pad_inches=+0.03, dpi=1000)
elif dpi is not None:
plt.savefig(filepath, dpi=dpi)
else:
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
index 3e7249c7..15750592 100644
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
@@ -289,7 +289,8 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
def visualize_trend_test_repartition_poster(self, reduction_function, axes=None, subtitle='', isin_parameters=None,
plot_title=None,
poster_plot=False,
- write_text_on_massif=True):
+ write_text_on_massif=True,
+ display_trend_color=True):
trend_type_to_serie = {k: v[0].replace(0.0, np.nan) for k, v in
self.trend_type_to_series(reduction_function, isin_parameters).items()}
@@ -324,7 +325,7 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
else:
mean_idx, variance_idx = 1, 2
- massif_to_value_for_trend_type = {k: "$t_0=$" + str(int(v)) for k, v in
+ massif_to_value_for_trend_type = {k: int(v) for k, v in
self.trend_type_to_series(reduction_function,
isin_parameters)[
display_trend_type][3].items()
@@ -356,19 +357,37 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
AbstractGevTrendTest.nb_years_for_quantile_evolution)
for m in massif_to_strength}
else:
- massif_name_to_value = massif_to_year
- self.study.visualize_study(None, massif_name_to_color=massif_to_color, show=False,
- show_label=False, scaled=True, add_text=write_text_on_massif,
- massif_name_to_value=massif_name_to_value,
- fontsize=4,
- axis_off=True,
- massif_name_to_hatch_boolean_list=massif_name_to_hatch_boolean_list)
+ massif_name_to_value = {k: "$t_0=$" + str(int(v)) if display_trend_color else v for k, v in massif_to_year.items()}
+
+ title = self.set_trend_test_reparition_title(subtitle, set=not poster_plot, first_title=display_trend_color)
+
+ if display_trend_color:
+ self.study.visualize_study(None, massif_name_to_color=massif_to_color, show=False,
+ show_label=False, scaled=True, add_text=write_text_on_massif,
+ massif_name_to_value=massif_name_to_value,
+ fontsize=4,
+ axis_off=True,
+ massif_name_to_hatch_boolean_list=massif_name_to_hatch_boolean_list,
+ )
+ else:
+ VMIN = 1957
+ VMAX = 1998
+ assert VMIN < self.first_starting_year
+ assert VMAX > self.last_starting_year
+ self.study.visualize_study(None, show=False,
+ show_label=False, scaled=True, add_text=False,
+ massif_name_to_value=massif_name_to_value,
+ cmap=plt.cm.GnBu,
+ add_colorbar=True,
+ vmin=VMIN,
+ vmax=VMAX)
+
+
- title = self.set_trend_test_reparition_title(subtitle, set=not poster_plot)
return title
- def set_trend_test_reparition_title(self, subtitle, set=True):
+ def set_trend_test_reparition_title(self, subtitle, set=True, first_title=True):
# Global information
title = 'Repartition of {} trends'.format(subtitle)
if self.study.has_orientation:
@@ -377,7 +396,7 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
if len(self.starting_years) > 1:
title += ' until starting_year={}'.format(self.last_starting_year)
title += ' with {} test'.format(get_display_name_from_object_type(self.trend_test_class))
- if self.reduce_strength_array:
+ if first_title:
title += '\nEvolution of the quantile {} every {} years'.format(AbstractGevTrendTest.quantile_for_strength,
AbstractGevTrendTest.nb_years_for_quantile_evolution)
else:
@@ -492,7 +511,8 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
isin_parameters=None,
show_or_save_to_file=True,
poster_plot=False,
- write_text_on_massif=True):
+ write_text_on_massif=True,
+ display_trend_color=False):
last_title = ''
for subtitle, reduction_function in self.subtitle_to_reduction_function(self.index_reduction,
level=self.massif_index_level,
@@ -501,7 +521,8 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
isin_parameters=isin_parameters,
plot_title=plot_title,
poster_plot=poster_plot,
- write_text_on_massif=write_text_on_massif)
+ write_text_on_massif=write_text_on_massif,
+ display_trend_color=display_trend_color)
if show_or_save_to_file:
self.show_or_save_to_file(specific_title=last_title, dpi=1000, tight=poster_plot)
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_full_hypercube.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_full_hypercube.py
index ffda9d8b..4ede274d 100644
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_full_hypercube.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_full_hypercube.py
@@ -22,7 +22,7 @@ def get_full_parameters(altitude=None, offset_starting_year=10):
altitudes = [altitude]
else:
altitudes = ALL_ALTITUDES[3:-6]
- first_starting_year = 1958 + offset_starting_year
+ first_starting_year = 1958
last_starting_year = 2017 - offset_starting_year
trend_test_class = GevLocationTrendTest
return altitudes, first_starting_year, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class
diff --git a/experiment/paper1_steps/poster_EVAN2019/main_poster_EVAN2019.py b/experiment/paper1_steps/poster_EVAN2019/main_poster_EVAN2019.py
index 4d65f079..063783cc 100644
--- a/experiment/paper1_steps/poster_EVAN2019/main_poster_EVAN2019.py
+++ b/experiment/paper1_steps/poster_EVAN2019/main_poster_EVAN2019.py
@@ -29,14 +29,18 @@ def main_poster_A_non_stationary_model_choice():
def main_poster_B_starting_years_analysis():
nb = 3
- for altitude in POSTER_ALTITUDES[2:]:
+ for altitude in POSTER_ALTITUDES[:nb]:
for trend_test_class in [GevLocationAndScaleTrendTest]:
# 1958 as starting year
vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
exact_starting_year=1958, reduce_strength_array=False,
trend_test_class=trend_test_class,
)
+ for d in [True, False]:
+ vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
+ display_trend_color=d)
# vizualiser.save_to_file = False
+
vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
# Optimal common starting year
vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=altitude,
@@ -48,13 +52,56 @@ def main_poster_B_starting_years_analysis():
vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
exact_starting_year=best_year, reduce_strength_array=False,
trend_test_class=trend_test_class)
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
+ for d in [True, False]:
+ vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
+ display_trend_color=d)
# Individual most likely starting year for each massif
vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
reduce_strength_array=False,
trend_test_class=trend_test_class,
offset_starting_year=20)
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=True)
+ for d in [True, False]:
+ vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
+ display_trend_color=d)
+
+# def main_poster_B_test():
+# nb = 3
+# for altitude in POSTER_ALTITUDES[:1]:
+# for trend_test_class in [GevLocationAndScaleTrendTest]:
+# # # 1958 as starting year
+# vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
+# exact_starting_year=1958, reduce_strength_array=False,
+# trend_test_class=trend_test_class,
+# )
+# # vizualiser.save_to_file = False
+# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
+# display_trend_color=False)
+# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
+# display_trend_color=True)
+# # # Optimal common starting year
+# vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=altitude,
+# reduce_strength_array=True,
+# trend_test_class=trend_test_class,
+# offset_starting_year=20)
+# res = vizualiser.visualize_year_trend_test(subtitle_specified='CrocusSwe3Days')
+# best_year = res[0][1]
+# vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
+# exact_starting_year=best_year, reduce_strength_array=False,
+# trend_test_class=trend_test_class)
+# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
+# display_trend_color=False)
+# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
+# display_trend_color=True)
+# # vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
+# # Individual most likely starting year for each massif
+# # vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
+# # reduce_strength_array=False,
+# # trend_test_class=trend_test_class,
+# # offset_starting_year=50)
+# # # vizualiser.save_to_file = False
+# # vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=True,
+# # display_trend_color=False)
+
def main_poster_C_orientation_analysis():
@@ -87,6 +134,6 @@ def main_poster_D_other_quantities_analysis():
if __name__ == '__main__':
# main_poster_A_non_stationary_model_choice()
- # main_poster_B_starting_years_analysis()
- main_poster_C_orientation_analysis()
+ main_poster_B_starting_years_analysis()
+ # main_poster_C_orientation_analysis()
# main_poster_D_other_quantities_analysis()
diff --git a/experiment/trend_analysis/univariate_test/abstract_univariate_test.py b/experiment/trend_analysis/univariate_test/abstract_univariate_test.py
index 7cbbf78e..1376adde 100644
--- a/experiment/trend_analysis/univariate_test/abstract_univariate_test.py
+++ b/experiment/trend_analysis/univariate_test/abstract_univariate_test.py
@@ -6,6 +6,7 @@ from collections import OrderedDict
import numpy as np
from cached_property import cached_property
+from matplotlib import colors
from experiment.trend_analysis.mann_kendall_test import mann_kendall_test
from experiment.trend_analysis.abstract_score import MannKendall
@@ -53,6 +54,11 @@ class AbstractUnivariateTest(object):
def three_main_trend_types(cls):
return [cls.SIGNIFICATIVE_NEGATIVE_TREND, cls.NON_SIGNIFICATIVE_TREND, cls.SIGNIFICATIVE_POSITIVE_TREND]
+ @classmethod
+ def rgb_code_of_trend_colors(cls):
+ for name in ['lightgreen', 'lightcoral', 'darkgreen', 'darkred']:
+ print(name, colors.to_rgba(name)[:-1])
+
@classmethod
def display_trend_type_to_style(cls):
d = OrderedDict()
@@ -143,3 +149,7 @@ class ExampleRandomTrendTest(AbstractUnivariateTest):
class WarningScoreValue(Warning):
pass
+
+
+if __name__ == '__main__':
+ AbstractUnivariateTest.rgb_code_of_trend_colors()
\ No newline at end of file
diff --git a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
index b605082f..6936b3fc 100644
--- a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
+++ b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
@@ -9,9 +9,8 @@ from extreme_estimator.margin_fits.extreme_params import ExtremeParams
from extreme_estimator.margin_fits.plot.shifted_color_map import shiftedColorMap
-def plot_extreme_param(ax, label: str, values: np.ndarray):
+def get_shifted_map(vmin, vmax):
# Load the shifted cmap to center on a middle point
- vmin, vmax = np.min(values), np.max(values)
if vmin < 0 < vmax:
midpoint = 1 - vmax / (vmax + abs(vmin))
elif vmin < 0 and vmax < 0:
@@ -22,29 +21,26 @@ def plot_extreme_param(ax, label: str, values: np.ndarray):
raise ValueError('Unexpected values: vmin={}, vmax={}'.format(vmin, vmax))
cmap = [plt.cm.coolwarm, plt.cm.bwr, plt.cm.seismic][1]
shifted_cmap = shiftedColorMap(cmap, midpoint=midpoint, name='shifted')
- norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
- norm = create_colorbase_axis(ax, label, shifted_cmap, norm)
- return norm, shifted_cmap
+ return shifted_cmap
def create_colorbase_axis(ax, label, cmap, norm):
divider = make_axes_locatable(ax)
- cax = divider.append_axes('right', size='5%', pad=0.03)
+ cax = divider.append_axes('right', size='5%', pad=0.0)
cb = cbar.ColorbarBase(cax, cmap=cmap, norm=norm)
if isinstance(label, str):
cb.set_label(label)
return norm
-def get_color_rbga_shifted(ax, replace_blue_by_white: bool, values: np.ndarray, label=None):
- """
- For some display it was necessary to transform dark blue values into white values
- """
- norm, shifted_cmap = plot_extreme_param(ax, label, values)
- m = cm.ScalarMappable(norm=norm, cmap=shifted_cmap)
+def get_norm(vmin, vmax):
+ return mpl.colors.Normalize(vmin=vmin, vmax=vmax)
+
+
+def get_colors(values, cmap, vmin, vmax, replace_blue_by_white=False):
+ norm = get_norm(vmin, vmax)
+ m = cm.ScalarMappable(norm=norm, cmap=cmap)
colors = [m.to_rgba(value) for value in values]
- # We do not want any blue values for parameters other than the Shape
- # So when the value corresponding to the blue color is 1, then we set the color to white, i.e. (1,1,1,1)
if replace_blue_by_white:
colors = [color if color[2] != 1 else (1, 1, 1, 1) for color in colors]
return colors
@@ -55,7 +51,10 @@ def imshow_shifted(ax, gev_param_name, values, visualization_extend, mask_2D=Non
if mask_2D is not None:
condition |= mask_2D
masked_array = np.ma.masked_where(condition, values)
- norm, shifted_cmap = plot_extreme_param(ax, gev_param_name, masked_array)
+ vmin, vmax = np.min(masked_array), np.max(masked_array)
+ shifted_cmap = get_shifted_map(vmin, vmax)
+ norm = get_norm(vmin, vmax)
+ create_colorbase_axis(ax, gev_param_name, shifted_cmap, norm)
shifted_cmap.set_bad(color='white')
if gev_param_name != ExtremeParams.SHAPE:
epsilon = 1e-2 * (np.max(values) - np.min(values))
@@ -64,4 +63,3 @@ def imshow_shifted(ax, gev_param_name, values, visualization_extend, mask_2D=Non
masked_array[-1, -1] = value - epsilon
# IMPORTANT: Origin for all the plots is at the bottom left corner
ax.imshow(masked_array, extent=visualization_extend, cmap=shifted_cmap, origin='lower')
-
--
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